Logic optimality for multi-objective optimization

Xiang Li

doi:10.1016/j.amc.2009.09.053

Logic optimality for multi-objective optimization

2009-12-01

17

PRE

AI

DOI：10.1016/j.amc.2009.09.053

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Pareto dominance is one of the most basic concepts in multi-objective optimization. However, it is inefficient when the number of objectives is large because in this case it leads to an unmanageable number of Pareto solutions. In order to solve this problem, a new concept of logic dominance is defined by considering the number of improved objectives and the quantity of improvement simultaneously, where probabilistic logic is applied to measure the quantity of improvement. Based on logic dominance, the corresponding logic nondominated solution is defined as a feasible solution which is not dominated by other ones based on this new relationship, and it is proved that each logic nondominated solution is also a Pareto solution. Essentially, logic dominance is an extension of Pareto dominance. Since there are already several extensions for Pareto dominance, some comparisons are given in terms of numerical examples, which indicates that logic dominance is more efficient. As an application of logic dominance, a house choice problem with five objectives is considered. (C) 2009 Elsevier Inc. All rights reserved.

Keyword:

Multi-objective optimization

Probabilistic logic

Pareto dominance

Logic dominance

Logic optimality for multi-objective optimization

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